Data Analysis · Retention Strategy Cross-functional · 3-person team

Aspire Institute:
Alumni Engagement
Analytics

Analyzed newsletter and weekly digest performance across multiple send cycles to find the content patterns driving alumni retention. Turned raw email data into strategy recommendations that contributed to an 18% improvement in alumni retention, and coordinated deliverables across a 3-person analyst team.

Alumni Engagement Dashboard Tableau · Google Sheets · Python
34.2%
Avg open rate
↑ career & events content
8.7%
Avg click-through rate
↑ after digest shortening
−18%
Digest click rate (long)
↓ inverse length relationship
+18%
Alumni retention
↑ post-recommendations
Open Rate by Content Type
Career
Events
News
Digest
Retention Improvement
18%
18% improvement in alumni retention after strategy recommendations rolled out across newsletter and digest channels.
+18%
Alumni retention improvement
3
Analysts coordinated into one deliverable
2
Channels analyzed, newsletter and weekly digest
Role
Data Analyst · Team of 3
Timeline
Apr – May 2024
Organization
Aspire Institute · Remote
Stack
Python · Tableau · Excel · Google Sheets
Context

The data existed; the analysis didn't.

Aspire Institute runs an alumni engagement program across newsletter and weekly digest channels. The data existed: multiple send cycles of open rates, click rates, and content performance records. What didn't exist was a structured analysis of which content drives engagement, where the funnel breaks down, and what the team should do differently.

I handled the analysis and the cross-team coordination that kept three independent analyses reading as one report.

What I Did

Question-first, then the data.

01
Defined the analytical question
Before opening a spreadsheet: what content drives clicks, and why? That question shaped what we segmented, visualized, and excluded.
02
Data cleaning and segmentation in Python and Excel
Cleaned the dataset, segmented by content type and send date, and found patterns in open and click performance: which content categories drove the highest engagement, how performance varied over time, and where the click funnel dropped off most.
03
Dashboard build in Tableau
Built dashboards for non-technical stakeholders: open rate trends over time, content performance by category, click-to-open conversion rates, and engagement comparisons between the newsletter and digest formats.
04
Cross-team coordination for a unified final report
Worked with two other analysts to merge our separate analyses into one deliverable. We set shared metric definitions early (what "click rate" means, what "engagement" counts) and a common visualization style, so the final report read as one analysis rather than three stitched together.
Key Findings

What the data showed.

Finding Signal Implication
Career and events content Highest open rates Alumni opened consistently when subject lines signaled professional development or upcoming events. Utility drove engagement.
General digest editions Lowest click-through Catch-all digests without a clear content hook performed poorly. Volume without focus diluted engagement.
Subject line specificity Correlated with opens Benefit-led subject lines consistently outperformed vague or date-based subject lines across all content types
Digest length vs. click rate Inverse relationship Longer digests showed lower click-to-open rates. Shorter, focused editions drove more action per reader.
Send timing Variable Inconsistent send times complicated performance analysis and made it harder to build reader habit
Recommendations

Four concrete changes.

Lead with career and events content
These two content types drove the highest engagement. Leading newsletters with career opportunities and upcoming events, ahead of general news, would increase the share of openers who click through.
Shorten and focus the weekly digest
The data showed an inverse relationship between digest length and click rate. Fewer, better-chosen items outperform longer digests with broad content. Recommended capping at 4–5 items with a clear primary CTA per send.
Rewrite subject lines around benefit, not description
Subject lines that led with what the reader would get ("3 opportunities for your career this week" vs. "Aspire Weekly Digest #47") consistently outperformed. Recommended a subject line framework built around specificity and utility.
Standardize send timing
Inconsistent send days made it hard to build reader habit and complicated performance analysis. A steady weekly cadence improves open rates and the reliability of future A/B testing.
Next Project
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